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De Place Hansen, E J and Larsen, J N (2011) Employment and winter construction: a comparative analysis of Denmark and western European countries with a similar climate. Construction Management and Economics, 29(09), 875–90.

Espinoza, R D (2011) Contingency estimating using option pricing theory: closing the gap between theory and practice. Construction Management and Economics, 29(09), 913–27.

Griffith, A (2011) Delivering best value in the small works portfolio of public sector organizations when using preferred contractors. Construction Management and Economics, 29(09), 891–900.

Jha, K N and Chockalingam, C T (2011) Prediction of schedule performance of Indian construction projects using an artificial neural network. Construction Management and Economics, 29(09), 901–11.

Jiang, H and Liu, C (2011) Forecasting construction demand: a vector error correction model with dummy variables. Construction Management and Economics, 29(09), 969–79.

McCabe, A, Parker, R and Brown, K (2011) Social outcomes in the construction industry: the case of the Western Australian ‘Percent for Art’ policy. Construction Management and Economics, 29(09), 929–41.

Styhre, A (2011) The overworked site manager: gendered ideologies in the construction industry. Construction Management and Economics, 29(09), 943-955.

Wakchaure, S S and Jha, K N (2011) Prioritization of bridges for maintenance planning using data envelopment analysis. Construction Management and Economics, 29(09), 957–68.

  • Type: Journal Article
  • Keywords: analytical hierarchy process; bridge; bridge health index; condition states; data envelopment analysis
  • ISBN/ISSN:
  • URL: http://www.tandfonline.com/doi/abs/10.1080/01446193.2011.614267
  • Abstract:
    Resources - especially funds allotted - for the maintenance of bridges, are generally scanty. Thus, it becomes difficult to select bridges for maintenance from among several competing bridges to ensure their safety and serviceability to the desired level. A bridge health index is considered a reasonably accurate depiction of the condition of a bridge and hence is the basis for most of the decisions on fund allocation. However, it still remains to be seen whether such a decision-making tool results in an efficient fund allocation. From data collected on Indian bridges, it is observed that fund allocation based on bridge condition is not always judicious. Rather, a number of factors affect the final decision on fund allocation. Hence, an alternative approach of data envelopment analysis (DEA) has been used for scoring the efficiency of 14 bridges selected for the study. Depending on the availability of data, this method can take into account other factors besides the bridge health index that influence decisions on maintenance planning. The variables selected for the DEA are: bridge health index, deck area of the bridge, maintenance cost of the bridge, and the age of the bridge. The allocation of funds for the maintenance of bridges based on DEA has proved to be comparatively more efficient. This has been illustrated with the help of a numerical example. The proposed method would enable bridge authorities to formulate better strategies for planning and executing bridge maintenance activities in a cost-effective manner.